We study an approximation for the zero-variance change of measure to estimate the probability of a rare event in a continuous-time Markov chain. The rare event occurs when the cha...
Pieter-Tjerk de Boer, Pierre L'Ecuyer, Gerardo Rub...
High-throughput analytical techniques such as nuclear magnetic resonance, protein kinase phosphorylation, and mass spectroscopic methods generate time dense profiles of metabolites...
Prospero C. Naval, Luis G. Sison, Eduardo R. Mendo...
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
In this work we present an improved evolutionary method for inferring S-system model of genetic networks from the time series data of gene expression. We employed Differential Ev...
The purpose of this work is to propose an immune-inspired setup to use a self-organizing map as a computational model for the interaction of antigens and antibodies. The proposed ...